Past trends in public health relevant characteristics of U.S. extreme heat events

Evan M. Oswald, Richard B. Rood

Motivation

1. Past changes in extreme heat event (EHE) risk

2. Assist in future forecasting of EHE risk

3. United States Historical Climate Network (USHCN) monthly dataset version 2-based trends

Hypotheses

1. Continental average trends exist

2. Regional-scale spatial structure exists in those trends

3. Extreme heat event trends are a function of which daily metric(s) used

4. Strong relationships with summer average temperature trends

Dataset

1. USHCN monthly dataset version 2

2. USHCN daily dataset version 1

3. Day-to-day variability transferred onto monthly values

4. Station selection criteria

Study details1. EHE def: 92.5th percentile, 2 dates, running mean > 92.5th percentile2. Types: Tmin, Tmax, “Tmnx”3. EHE Characteristics:

1. All encompassing metrics: No. EHE days per summer, sum intensity

2. Specific EHE characteristics: mean duration, mean intensity, No. EHEs per summer

3. Special interest metrics: No. of EHE days before July 1st

Continental averagesEH

E ch

arac

teris

tics

EHE type

Spatial Maps(1970-2010)

Tmin type

Tmnx type

Tmax type

Spatial MapsSpatial Maps(1930-2010)

Tmin type

Tmnx type

Tmax type

Longer trends = bigger decrease, smaller increase

Relationship with summer mean trends

Relationship with early season events

Conclusions

1. Continental averages

a) Increasing trends: 1970-2010

b) Small trends: 1930-2010

2. Spatial structure

a) Upper midwest / Eastern Central US feature.

3. Relationships

a) Characteristics

b) Different daily extremes

c) Seasonal averages

d) Early season

Things to think about

1. Climatologists

a) Mapping data of different temporal resolutions

b) Warming hole, extreme temperatures

c) Trend sensitivity (distribution, season)

2. End-users

a) EHE definition: daily extreme sensitivity

b) Trend sensitivity

c) Summer average vs summertime EHE trends

d) Early season vs summertime EHE trends